Introduction:The current American Joint Committee on Cancer (AJCC) M1a staging of non-small cell lung cancer (NSCLC) encompasses a wide disease spectrum, showing diverse prognosis. Methods: Patients who diagnosed in an earlier period formed the training cohort, and those who diagnosed thereafter formed the validation cohort. Kaplan-Meier analysis was performed for the training cohort by dividing the M1a stage into three subgroups: (I) malignant pleural effusion (MPE) or malignant pericardial effusion (MPCE); (II) separate tumor nodules in contralateral lung (STCL); and (III) pleural tumor nodules on the ipsilateral lung (PTIL). Gender, age, histologic, N stage, grade, surgery for primary site, lymphadenectomy, M1a groups, and chemotherapy were selected as independent prognostic factors using the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. And a nomogram was constructed using Cox hazard regression analysis. Accuracy and clinical practicability were separately tested by Harrell's concordance index, the receiver operating characteristic (ROC) curve, calibration plots, residual plot, the integrated discrimination improvement (IDI), net reclassification improvement (NRI), and decision curve analysis (DCA). Results: The concordance index (0.661 for the training cohort and 0.688 for the validation cohort) and the area under the ROC curve (training cohort: 0.709 for 1-year and 0.727 for 2-year OS prediction; validation cohort: 0.737 for 1-year and 0.734 for 2-year OS prediction) indicated satisfactory discriminative ability of the nomogram. Calibration curve and DCA presented great prognostic accuracy, and clinical applicability. Its prognostic accuracy preceded the AJCC staging with evaluated NRI (1-year: 0.327; 2-year: 0.302) and IDI (1-year: 0.138; 2-year: 0.130). Conclusion: Our study established a nomogram for the prediction of 1-and 2year OS in patients with NSCLC diagnosed with stage M1a, facilitating healthcare How to cite this article: Chen H, Huang C, Ge H, et al. A novel LASSO-derived prognostic model predicting survival for non-small cell lung cancer patients with M1a diseases.

Background. Bone metastasis (BM) has been proven to be responsible for the poor prognosis of primary malignant bone neoplasms (PMBNs). We aimed to identify the prevalence, risk factors, and prognostic factors for PMBNs patients with BM based on the Surveillance, Epidemiology, and End Results (SEER) database. Methods. 4,758 patients diagnosed with PMBNs from 2010 to 2018 were selected from the SEER database. All patients were divided into two groups: the BM group or the non-BM group. Pearson’s chi-square test and Fisher’s exact method were used to assess baseline characteristics, and logistic regression analysis was applied to assess risk factors. In addition, a nomogram was constructed based on the results of Cox regression analysis among 227 patients with BM. The good performance and clinical applicability of the nomogram were tested by the concordance index, operating characteristic curve, area under the curve, calibration curves, and decision curve analysis. Results. 227 (4.8%) patients had metastasis to bone at diagnosis. Primary site outside the extremities (axial: odds ratio, OR = 1.770 ; others: OR = 1.951 ), Ewing sarcoma ( OR = 2.845 ), larger tumor size (5–8 cm: OR = 3.403 ; >8 cm: OR = 5.562 ), tumor extension beyond the periosteum ( OR = 2.477 ), and regional lymph node metastasis ( OR = 2.900 ) were associated with a higher risk of BM at the initial diagnosis of PMBNs. Five independent prognostic factors were found in the survival analysis: pathological type (chondrosarcoma vs. osteosarcoma: hazard ratio, HR = 0.342 ; Ewing sarcoma vs. osteosarcoma: HR = 0.592 ; and chordoma vs. osteosarcoma: HR = 0.015 ), marital status ( HR = 2.457 ), pulmonary metastasis ( HR = 1.934 ), surgery at the primary site ( HR = 0.164 ), and chemotherapy ( HR = 0.084 ). A nomogram based on these prognostic factors could be a good predictor of cancer-specific survival. Conclusions. We identified the prevalence, risk factors, and prognostic factors correlated with BM in PMBNs patients. The related nomogram could be a practical tool for therapeutic decision-making and individual counseling.